FHE Accelerator Memory Mapping and NTT Layout for Key Switching
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Solution Overview
Problem
Existing fully homomorphic encryption (FHE) systems face challenges in efficiently processing encrypted data due to noise growth, ciphertext expansion, and high computational overhead, particularly in operations like bootstrapping and key switching, which dominate computation and data movement costs.
Innovation Solution
A dedicated hardware accelerator system is designed to optimize FHE operations by employing a conflict-free memory access mechanism, high-radix NTT processing, and on-the-fly generation of twiddle factors and key-switching keys, utilizing parallelism at the coefficient level to minimize noise growth and reduce memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional software-based FHE processing is used, then security and privacy are maintained through encryption, but computational overhead and processing time increase significantly
Solution Approach 1:
The patent replaces software-based FHE computations with dedicated hardware circuits implemented on an FPGA. The hardware accelerator includes specialized modules for homomorphic addition, multiplication, and bootstrapping operations, substituting the mechanical/software execution model with an electronic/hardware model that provides parallel processing capability and constant-time operations, thereby maintaining security while dramatically improving processing speed.
Solution Approach 2:
The hardware accelerator implements self-service through automated key management and on-the-fly key switching capabilities. The system includes dedicated key storage registers and key switching logic that automatically perform cryptographic key operations without requiring external software intervention, reducing overhead and enabling the FHE operations to service themselves efficiently at hardware speed.
2Measurement precision
If bootstrapping operations are performed to manage noise growth, then decryption accuracy is maintained, but computation time and data movement costs increase
Solution Approach 1:
The patent implements preliminary action by pre-computing and storing bootstrapping parameters and lookup tables in hardware registers before they are needed. The bootstrapping module is pre-configured with the necessary cryptographic parameters and noise management data, allowing the system to perform bootstrapping operations quickly when noise thresholds are approached, maintaining decryption accuracy while minimizing the time penalty through pre-prepared hardware resources.
3Reliability
If key switching is performed frequently to manage ciphertext noise, then encryption security is maintained, but memory bandwidth and computational resources are consumed
Solution Approach 1:
The patent applies segmentation by dividing the key switching operation into separate, specialized hardware modules: key storage registers, key switching control logic, and ciphertext transformation units. This segmentation allows key switching to be performed in a controlled, efficient manner with dedicated pathways for key material and ciphertext data, reducing unnecessary memory accesses and optimizing the use of memory bandwidth while maintaining encryption security.
Data Source
AI summary
A device for processing homomorphically encrypted data, preferably including a memory, a number-theoretic transform processing element, and/or a multiply-accumulate processing element. The memory can preferably be accessed by row or column through XOR-based address mapping procedures performed at a permutation processing element that preferably converts data between conflict-free memory bank ordering and natural ordering, such as wherein the device can receive input data to be stored in the memory and/or send output data from the memory to a processing board. The multiply-accumulate processing element can preferably perform a key-switching operation using a key-switching key and the input data, wherein a first half of the key-switching key is randomly generated at a random number generator. The multiply-accumulate processing element can include a command input with pipeline stages, a register file, a plurality of multiplexers, a multiplier, and/or an adder.